In a radio communication system, a sender and a receiver achieve a higher rate by virtue of multiple antennae in a spatial multiplexing manner. Compared with a general spatial multiplexing method, an enhanced technology is that a receiver feeds back channel information to a sender and the sender adopts certain sending precoding technologies according to the obtained channel information, so that transmission performance can be greatly improved. For Single-User Multi-input Multi-output (SU-MIMO), channel feature vector information is directly adopted for precoding. While for Multi-User MIMO (MU-MIMO), relatively accurate channel information is required.
In a Long Term Evolution (LTE) project, a simple single-codebook feedback method is mainly adopted for feedback of channel information, and performance of a sending precoding technology for MIMO is more dependent on accuracy of codebook feedback.
A basic principle of codebook-based channel information quantization feedback is briefly elaborated below.
If limited capacity of a feedback channel is B bps/Hz, the number of available code words is N=2B. A feature vector space of a channel matrix is quantized into a codebook space ={F1,F2 . . . FN}. Both a sender and a receiver store or generate in real time the codebook (the codebook is the same at the sender and the receiver). The receiver selects a code word {circumflex over (F)} most matched with the channel from  according to a certain criterion and the channel matrix H obtained by the receiver, and feeds back a code word index i to the sender. Here, the code word index is called a Precoding Matrix Indicator (PMI). The sender finds the corresponding precoding code word {circumflex over (F)} according to the index i, thereby obtaining channel information, {circumflex over (F)} representing feature vector information of the channel.
Generally,  may further be divided into codebooks corresponding to multiple ranks, and each rank corresponds to multiple code words for quantizing a precoding matrix formed by channel feature vectors under this rank. Since the number of ranks is equal to the number of non-zero feature vectors of a channel, there should be N columns in each code word when the rank is N. Therefore, codebook  may be divided into multiple sub-codebooks according to different ranks, as shown in Table 1, which is a schematic table of division of codebook  into multiple sub-codebooks according to different ranks in a related technology.
TABLE 1   Number of layers ν (rank)12. . .N   1  2. . .  NSet of code wordSet of code word. . .Set of code wordvectors with onematrixes with twomatrixes with Ncolumncolumnscolumns
In Table 1, 1 represents a set of code word vectors with one column, 2 represents a set of code word matrixes with two columns, and N represents a set of code word matrixes with N columns.
A matrix form is adopted for all of code words to be stored when rank>1, wherein this codebook quantization feedback method is adopted for a codebook in LTE protocol. Table 2 is a schematic table of codebooks of 4 LTE downlink sending antennae in the related technology. As shown in Table 2, a precoding codebook and channel information quantization codebook in LTE practically have the same meaning. In order to implement unification, a vector may also be considered as a one-dimensional matrix hereinafter.
TABLE 2Code Total number of layers ν (RI)word indexun12340u0 = [1 −1 −1 −1]TW0{1}W0{14}/√2W0{124}/√3W0{1234}/21u1 = [1 −j 1 j]TW1{1}W1{12}/√2W1{123}/√3W1{1234}/22u2 = [1 1 −1 1]TW2{1}W2{12}/√2W2{123}/√3W2{3214}/23u3 = [1 j 1 −j]TW3{1}W3{12}/√2W3{123}/√3W3{1234}/24u4 = [1 (−1 − j)/√2 − j (1 − j)/√2]T W4{1}W4{14}/√2W4{124}/√3W4{1234}/25u5 = [1 (1 − j)/√2 j (−1 − j)/√2]TW5{1}W5{14}/√2W5{124}/√3W5{1234}/26u6 = [1 (1 + j)/√2 − j (−1 + j)/√2]TW6{1}W6{13}/√2W6{134}/√3W6{1324}/27u7 = [1 (−1 + j)/√2 j (1 + j)/√2]TW7{1}W7{13}/√2W7{134}/√3W7{1324}/28u8 = [1 −1 1 1]TW8{1}W8{12}/√2W8{124}/√3W8{1234}/29u9 = [1 −j −1 −j]TW9{1}W9{14}/√2W9{134}/√3W9{1234}/210u10 = [1 1 1 −1]TW10{1}W10{13}/√2W10{123}/√3W10{1324}/211u11 = [1 j −1 j]TW11{1}W11{13}/√2W11{134}/√3W11{1324}/212u12 = [1 −1 −1 1]TW12{1}W12{12}/√2W12{123}/√3W12{1234}/213u13 = [1 −1 1 −1]TW13{1}W13{13}/√2W13{123}/√3W13{1324}/214u14 = [1 1 −1 −1]TW14{1}W14{13}/√2W14{123}/√3W14{3214}/215u15 = [1 1 1 1]TW15{1}W15{12}/√2W15{123}/√3W15{1234}/2
In Table 2, Wn=I−2ununH/unHun, I is a unit matrix, Wk(j) represents a vector in column j of matrix Wk, and Wk(f1,f2, . . . fn) represents a matrix formed by columns j1,j2, . . . , jn of matrix Wk.
The principle of a codebook feedback technology in LTE is introduced above, and during practical application, some more specific feedback methods will be further involved.
A feedback granularity of channel information is introduced at first. In an LTE standard, a minimum feedback unit of channel information is subband channel information, one subband consists of a certain number of Resource Blocks (RBs), each RB consists of multiple Resource Elements (REs), and RE is a minimum unit of a time-frequency resource in LTE. A resource representation method for LTE is also adopted for LTE-Advanced (LTE-A). A few subbands may be called multi-subband, while a large number of subbands may be called wideband.
A feedback content related to channel information in LTE is introduced below.
CSI feedback includes: Channel Quality Indication (CQI) information, a PMI and a Rank Indicator (RI). A CSI content that is concerned about most here is PMI information, but the RI and CQI are both feedback contents related to the CSI.
CQI is an index for evaluating quality of a downlink channel. CQI is represented by an integral value of 0˜15, which indicate different CQI levels respectively, in protocol 36-213, and different CQI corresponds to respective Modulation and Coding Schemes (MCSs).
An RI is used for describing the number of spatial independent channels, and corresponds to a rank of a channel response matrix. UE is required to feed back RI information in both open loop spatial multiplexing and closed loop spatial multiplexing modes, and is not required to feed back RI information in other modes. The rank of the channel matrix corresponds to the number of layers.
Some mechanisms related to channel information feedback in LTE are further introduced.
There are two feedback manners for uplink channel information in LTE: periodic channel information feedback on a Physical Uplink Control Channel (PUCCH) and non-periodic channel information feedback on a Physical Uplink Shared Channel (PUSCH). The PUCCH is a control channel with higher feedback reliability, but the feedback resource for the PUCCH is precious and feedback overhead is strictly limited. The amount of CSI (including one or more of PMIs, CQI and RIs) fed back once usually should not exceed 11 bits. The PUSCH may provide more CSI feedback resources, but the reliability of feedback on the PUSCH cannot be ensured, moreover, since a data transmission resource is required to be occupied, the CSI feedback on the PUSCH has some influence on transmission of a data service.
Along with rapid development of radio communication technologies, there are more and more radio applications for users, which promote rapid increase of radio data services. It is predicted that data services will be increased at a rate of 1.6 to 2 times every year in the next 10 years, which brings great challenge to the radio access network. A multi-antenna technology is a key technology for dealing with the challenge of explosive increase of radio data services, a current multi-antenna technology supported in 4-Generation (4G) communication only supports a technology for horizontal-dimension beamforming of at most 8 ports, and there is a great potential to further improve system capacity greatly.
A Massive MIMO technology is a key enhanced technology in next-generation communication technologies, and a Massive MIMO system has a main characteristic that: an eNodeB side is configured with a large-scale antenna array including, for example, 100 antennae or even more, multiple users are simultaneously multiplexed under the same frequency by virtue of an MU-MIMO technology during data transmission, and a proportion of the number of the antennae to the number of the multiplexed users is usually kept about 5-10. It can be proved that a correlation coefficient between channels of any two users is exponentially attenuated along with increase of the number of the antennae, no matter whether the channels are strongly-correlated channels in a line-of-sight environment or uncorrelated channels under rich scattering environment. For example, when the eNodeB side is configured with 100 antennae, a correlation coefficient between channels of any two users is approximate to 0, that is, corresponding channels of multiple users are approximately orthogonal. On the other hand, a large array can bring considerable array gains and diversity gains.
For Massive MIMO, due to introduction of massive antennae, a conventional method is that: each antenna sends a Channel State Information-Reference Signal (CSI-RS), UE detects the CSI-RS, obtains a channel matrix corresponding to each transmission resource by channel estimation, obtains the precoding vector of each frequency-domain subband on an optimal baseband and information about the number of optimal transmission layers on a wideband according to the channel matrixes, and performs feedback on the basis of the codebook feedback technology introduced before.
However, such a manner has a big problem during application of Massive MIMO, specifically, code words are difficult to select to cause increase of complexity of the UE and even incapability or high cost in implementation because a codebook adopted for feedback needs to include a very large number of code words. Under such a condition, the overhead for codebook feedback is also high, so that uplink overhead is dramatically increased.
Therefore, application of a codebook-based CSI feedback manner to Massive MIMO may cause the problems of difficulty in code word selection and increase of link overhead in the related technology.